Re: [Rd] Manipulating single-precision (float) arrays in .Call functions

From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>
Date: Tue, 19 Jul 2011 07:26:08 +0100 (BST)

On Mon, 18 Jul 2011, Alireza Mahani wrote:

> Simon,
>
> Thank you for elaborating on the limitations of R in handling float types. I
> think I'm pretty much there with you.
>
> As for the insufficiency of single-precision math (and hence limitations of
> GPU), my personal take so far has been that double-precision becomes crucial
> when some sort of error accumulation occurs. For example, in differential
> equations where boundary values are integrated to arrive at interior values,
> etc. On the other hand, in my personal line of work (Hierarchical Bayesian
> models for quantitative marketing), we have so much inherent uncertainty and
> noise at so many levels in the problem (and no significant error
> accumulation sources) that single vs double precision issue is often
> inconsequential for us. So I think it really depends on the field as well as
> the nature of the problem.

The main reason to use only double precision in R was that on modern CPUs double precision calculations are as fast as single-precision ones, and with 64-bit CPUs they are a single access. So the extra precision comes more-or-less for free. You also under-estimate the extent to which stability of commonly used algorithms relies on double precision. (There are stable single-precision versions, but they are no longer commonly used. And as Simon said, in some cases stability is ensured by using extra precision where available.)

I disagree slightly with Simon on GPUs: I am told by local experts that the double-precision on the latest GPUs (those from the last year or so) is perfectly usable. See the performance claims on http://en.wikipedia.org/wiki/Nvidia_Tesla of about 50% of the SP performance in DP.

>
> Regards,
> Alireza
>
>
> --
> View this message in context: http://r.789695.n4.nabble.com/Manipulating-single-precision-float-arrays-in-Call-functions-tp3675684p3677232.html
> Sent from the R devel mailing list archive at Nabble.com.
>
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-- 
Brian D. Ripley,                  ripley_at_stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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